The high economic burden of ADHD and psychiatric comorbidities throughout the lifespan

Home | The high economic burden of ADHD and psychiatric comorbidities throughout the lifespan

6 Feb 2019

Libutzki B et al. Eur Psychiatry 2019; 58: 38-44

The economic burden of childhood and adolescent ADHD is reported to be high throughout a patient’s lifespan (Gupte-Singh K et al. 2017). Despite this, further research is needed to investigate the direct and indirect costs associated with ADHD; for example, the direct cost of ADHD is much less well understood in adults compared with children, and although ADHD is associated with multiple psychiatric comorbidities in both childhood and adulthood, studies presenting indirect costs due to these co-occurring conditions have not yet been conducted. In adulthood, obesity, substance-use disorder (SUD), mood disorders and anxiety disorders are frequently associated with ADHD; therefore, detailed cost estimations of ADHD and comorbidities are of relevance to health insurers as well as national economies, so as to identify gaps in care for patients with ADHD and to develop preventative measures or programmes to address these gaps. The aim of this study was to assess the overall direct medical costs of ADHD and to determine the surplus costs of comorbid obesity, SUD, mood and anxiety disorders, each stratified by age and gender.

Using claims data from a German Statutory Health Insurance database, which insures approximately 90% of the German population, patients with ADHD diagnosed according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) were identified.* An age- and gender-adjusted reference group without ADHD was randomly selected and matched 1:1 to patients with ADHD. Total health claims and healthcare costs associated with ADHD (mean costs per patient) were analysed, as well as the occurrence rates and costs of obesity, SUD, mood and anxiety disorders comorbid with ADHD. Additional costs of comorbid conditions in patients with ADHD were compared with those in individuals without ADHD, and subgroup analyses were conducted based on age (0–12 years, 13–17 years, 18–30 years and ≥31 years) and gender.

A total of 3,705,952 individuals were included in the database and of these, 25,300 had ADHD (male: n = 18,714; female: n = 6586), indicating an overall lifespan prevalence of 0.68%. Prevalence estimates per age group were as follows: 2.89% for 0–12 years; 4.13% for 13–17 years; 0.66% for 18–30 years; and 0.08% for ≥31 years. On average, males diagnosed with ADHD were 14.7 (standard deviation [SD] ± 8.8) years old and females were 17.7 (SD ± 12.9) years old. These data indicate that based on this claims database, the prevalence of ADHD was higher in younger patients.

ADHD was associated with significantly higher healthcare costs when compared with costs for individuals without ADHD, with a surplus cost of €1508 per patient across all age groups (p < 0.001). Hospital costs accounted for ~43% of this surplus cost, with additional costs of €648 per patient per year. Visits to psychiatrists were the second-largest cost (16% of total surplus cost; €243), followed by stimulant costs (11% of total surplus cost; €168). Other costs included: visits to a psychotherapist (9%; €130), occupational therapy (8%; €127), visits to a general practitioner (7%; €111), remedies (3%; €47), sick payment (2%; €34) and aid costs (0.6%; €9). In terms of ‘other drugs’, lower costs were associated with patients with ADHD (–€8) compared with individuals without ADHD. The ADHD group associated with the highest costs were ≥31 years old, with costs of €3402 compared with €1220 for individuals without ADHD. Stimulant costs were highest for adolescents with ADHD (aged 13–17 years), with a cost of €215 compared with €151 and €181 for adults with ADHD aged 18–30 years and ≥31 years, respectively.

Compared with individuals without ADHD, patients with ADHD were more likely to have comorbid SUD (n = 324 vs 1097; odds ratio [OR] 3.5), obesity (n = 1140 vs 2041; OR 1.9), mood disorders (n = 639 vs 3231; OR 5.7) and anxiety disorders (n = 1962 vs 6417; OR 4.0). In patients with ADHD, SUD was more prevalent in females (OR 3.7) than in males (OR 3.4); this effect was most apparent in patients with ADHD aged 13–17 years. The OR for obesity was similar between females and males with ADHD (1.8 vs 1.9), but the ORs for mood and anxiety disorders were higher in male than in females (mood disorders: 6.4 vs 5.0; anxiety disorders: 4.4 vs 3.7). The occurrence of SUD, obesity, mood and anxiety disorders increased with age in patients with ADHD and also for individuals without ADHD. Mood disorders occurred 4–9-times more frequently, and anxiety disorders occurred 2–4-times more frequently in patients with ADHD aged ≥31 years compared with those without ADHD. These data indicate that 65% of males and 70% of females with ADHD aged ≥31 years in this sample had mood or anxiety disorders. The higher incidence of SUD, obesity, anxiety and mood disorders in patients with ADHD was associated with higher surplus comorbidity-related costs compared with individuals without ADHD but with the same condition. The highest surplus costs were associated with female patients with ADHD for SUD (female: €2821; male: €2610) and obesity (female: €2038; male: €1621). On the other hand, surplus costs associated with mood and anxiety disorders were higher for males than for female patients with ADHD (mood disorders: €1876 vs €963; anxiety disorders: €1792 vs €1535). Surplus costs for SUD or mood disorders were highest in female patients with ADHD aged between 13–17 years, whereas surplus costs for obesity and anxiety disorders were highest in female patients with ADHD aged ≥31 years. The highest surplus cost in male patients with ADHD aged ≥31 years was for SUD; surplus costs for mood and anxiety disorders were highest in males aged 0–12 years.

There were several limitations to this study. The first is that only four comorbid conditions were included in the study, and additionally comorbid obesity was likely underestimated since only individuals diagnosed with morbid obesity were included. Moreover, these selected comorbidities do not capture all comorbidities associated with ADHD. Additionally, the prevalence of ADHD in this study could only be assessed administratively, as opposed to epidemiologically. This may have led to a systematic underestimation of patients with ADHD, as only documented and diagnosed patients with ADHD were included. Moreover, the surplus costs of ADHD adjusted for the general population may be substantially lower than reported here, since diagnosed patients captured in this claims database may have had more severe ADHD, which could be more cost-intensive than less severe forms of ADHD. Other minor limitations were that out-of-pocket payments were not included in the cost estimates, only patients with ADHD diagnosed according to the ICD-10 were included in the study, and only individuals who were continuously insured during the observation period were included in the analyses.

The authors concluded that these data suggest that the cost of ADHD is high and that comorbid conditions are important cost-drivers. A gap in care was also identified in patients with ADHD aged ≥17 years, as the costs associated with a patient with ADHD during adolescence decreased from childhood; this was also associated with a drop in administrative prevalence of ADHD, indicating that better co-operation between different types of care providers may be required to ensure continuous treatment of ADHD symptoms during adolescence and adulthood. The authors also suggested that in the future, use of managed care programmes should be implemented to improve situation of care and simultaneously reduce costs in patients with ADHD, and that this should be based on detailed knowledge of age- and gender-specific cost-drivers.

*Routine billing data over a period of 6 years (2009–2014) were analysed; an individual must have had at least one inpatient or day-patient main diagnosis of ADHD, or two outpatient ADHD diagnoses (according to ICD-10 codes F90.0, F90.1 and F90.8) in three different quarters of the year to be included in the study

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